FinalYearKitFinalYearKit
AI / ML

Traffic Sign Recognition

Classify traffic sign images with a CNN — a computer vision kit with a clean Streamlit demo.

PythonTensorFlow/KerasStreamlitOpenCV
chat.py
What sign is in this photo?
Predicted: Speed Limit 60 (0.93). Alternatives: Speed Limit 80 (0.04), End of limit (0.02).
Predict → Result
TESTED

What it does

Upload a traffic sign image and get the predicted class with confidence. Includes a labeled sample set and training notebook/script so you can explain CNN layers and data augmentation in viva.

Features

  • ✓Image upload → sign class prediction
  • ✓Top-k confidence display
  • ✓Sample sign gallery for demos
  • ✓Training accuracy/loss charts

What's included

  • ✓Full working Streamlit application
  • ✓8-chapter Word report
  • ✓14-slide presentation deck
  • ✓Viva question bank + cheat sheet
  • ✓Sample images and model weights

Pricing

Same pricing tiers across every project kit.

A freelancer would charge ₹10,000–₹20,000 for the same project. Our kits start at ₹1,499 and are delivered in hours — not weeks.

Starter

The working application, ready to run and demonstrate.

₹1,499₹2,500
Delivered within 4 hours via WhatsApp
  • ✓Full source code
  • ✓Setup & run instructions
  • ✓requirements.txt / package.json
  • ✓Runs on your machine in under 10 min
Get Starter kit
Most Popular

Standard

Submit-ready — full academic report and presentation included.

₹2,499₹4,500
Save ₹2,001
Delivered within 4 hours via WhatsApp
  • ✓Everything in Starter
  • ✓8-chapter Word report
  • ✓14-slide presentation deck
  • ✓Architecture & flow diagrams
Get Standard kit
Best Value

Complete

Everything to submit AND confidently defend your project.

₹3,499₹6,000
Save ₹2,501
Delivered within 6 hours via WhatsApp
  • ✓Everything in Standard
  • ✓Viva Q&A bank + cheat sheet
  • ✓Customized to your name & college
  • ✓WhatsApp support until submission
Get Complete kit

Satisfaction guarantee

Not happy with what you receive? Message us within 24 hours and we'll either fix it or refund you — no questions asked.

Questions about this project

Is this related to self-driving cars?+

It's a focused classification module — perfect scope for a semester project without claiming a full AV stack.

Can I use my own photos?+

Yes — results vary with angle/lighting; the report covers preprocessing tips.

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